Autoregression models of EEG. Results compared with expectations for a multilinear near-equilibrium biophysical process.
This paper considers the properties of parameters (natural frequencies and damping coefficients) obtained from segment-by-segment autoregression analysis of ECoG of rat. The use of a reference signal as control for parameter estimate errors, and multiple regression analyses indicate that the dependencies among parameters calculated from ECoG in the alert (desynchronised) state are of a form consistent with imposition of time-invariance assumptions (implicit in autoregression) on an inherently non-stationary, multimodal, linear and near-equilibrium "thermal" process.
Wright
J J
JJ
Department of Psychiatry and Behavioural Science, School of Medicine, University of Auckland, New Zealand.
Kydd
R R
RR
Sergejew
A A
AA
D000818:Animals; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D004569:Electroencephalography; D008297:Male; D008959:Models, Neurological; D051381:Rats; D011919:Rats, Inbred Strains; D012044:Regression Analysis